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The recent REACH regulations require the elimination of bisphenol-A and titanium dioxide from commercially available boron-based polymers. This has led to changes in some of the mechanical characteristics, which strongly influence the properties of magnetoactive borosilicate polymers. This work delivers results on the electrical properties and discusses some implications for future research using bisphenol-A and titanium-dioxide-free substitutes.
Transmission spectra of wet human teeth and dentin slices, together with blood of different flow rates were investigated over a wide spectral range, from visible to terahertz (THz) light. The results make it possible to find the optimum light frequency for an all-optical determination of pulpal blood flow and, consequently, for clinically diagnosis of tooth vitality.
Mechanical cues such as extracellular matrix stiffness and movement have a major impact on cell differentiation and function. To replicate these biological features in vitro, soft substrata with tunable elasticity and the possibility for controlled surface translocation are desirable. Here we report on the use of ultra-soft (Young’s modulus <100 kPa) PDMS-based magnetoactive elastomers (MAE) as suitable cell culture substrata. Soft non-viscous PDMS (<18 kPa) is produced using a modified extended crosslinker. MAEs are generated by embedding magnetic microparticles into a soft PDMS matrix. Both substrata yield an elasticity-dependent (14 vs. 100 kPa) modulation of α-smooth muscle actin expression in primary human fibroblasts. To allow for static or dynamic control of MAE material properties, we devise low magnetic field (≈40 mT) stimulation systems compatible with cell-culture environments. Magnetic field-instigated stiffening (14 to 200 kPa) of soft MAE enhances the spreading of primary human fibroblasts and decreases PAX-7 transcription in human mesenchymal stem cells. Pulsatile MAE movements are generated using oscillating magnetic fields and are well tolerated by adherent human fibroblasts. This MAE system provides spatial and temporal control of substratum material characteristics and permits novel designs when used as dynamic cell culture substrata or cell culture-coated actuator in tissue engineering applications or biomedical devices.
The proposed method allows a robot to quantify tactile recognition of grasped objects. The responses by the robot are matched by randomly introducing objects following the completion of tactile sensor based training phases on 4 specific objects. The reproduction of the robotic contact identification is accomplished by matching threshold values of the smallest eigenvalue of the Quadric surface - called the eigenvalue trajectory. Once the grasped objects are introduced to the 2-fingered robot hand, the eigenvalue trajectory of contact surfaces are calculated by the system. Calculations are based on the degree of similarity of the characteristics between the newly received and previously trained tactile data. Experimental results indicate that the proposed algorithm allows a successful quantification of robotic contact recognition and the accomplishment of high levels of accuracy in contact identification. These results confirm that the proposed method is useful for identifying contact surfaces based on tactile sensor data.
Piezoelectric actuators are well established for use in expensive optical equipment. Within the last decade, relatively inexpensive piezoelectric actuators have become established technology in pneumatic switching and the first piezoelectrically driven impactive robot grippers are just starting to emerge. Although this article concentrates largely on the use of piezoelectric actuators for use in robot gripping systems, the potential for applications outside this field is immense.
Shape memory materials fulfill an important role in both actuation and mechanical coupling between actuators and associated dynamic systems. The simplest techniques are thermally based and in addition to the more common shape memory alloys there are also shape memory polymers. These have similar characteristics to those of their metallic cousins, but there the relationship stops. The basic physical principles are very different and this paper attempts to outline the current state-of-the-art to those already involved with the technology and perhaps open a fresh chapter in smart materials to those who are new to it.
The magnetoelectric response of bi- and symmetric trilayer composite structures to pulsed magnetic fields is experimentally investigated in detail. The structures comprise layers of commercially available piezoelectric (lead zirconate titanate) and magnetostrictive (permendur or nickel) materials. The magnetic-field pulses have the form of a half-wave sine function with duration of 450 µs and amplitudes ranging from 500 Oe to 38 kOe. The time dependence of the resulting voltage is presented and explained by theoretical estimations. Appearance of voltage oscillations with frequencies much larger than the reciprocal pulse length is observed for sufficiently large amplitudes (~1-10 kOe) of the magnetic-field pulse. The origin of these oscillations is the excitation of bending and planar acoustic oscillations in the structures. Dependencies of the magnetoelectric voltage coefficient on the excitation frequency and the applied magnetic field are calculated by digital signal processing and compared with those obtained by the method of harmonic field modulation. The results are of interest for developing magnetoelectric sensors of pulsed magnetic fields as well as for rapid characterization of magnetoelectric composite structures.
This paper proposed a contact recognition algorithm capable of determining contact surfaces types by tactile sensor fusion. This algorithm can recognize grasped objects using a 2- fingered robot hand, on which tactile sensors are mounted. Experiments have demonstrated reliable surface classification and accurate transformation independent of object shape and orientation. The contribution of this paper regards the relations between a surface and the points cloud defining it. Particularly, we investigate on the possibility that there is some intrinsic feature of a points cloud under quadric surface, allowing us to discriminate or classify a dataset defining a surface from the acquisition noise.